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A cycle generative adversarial network for generating synthetic contrast-enhanced computed tomographic images from non-contrast images in the internal jugular lymph node-bearing area.
Fukuda, Motoki; Kotaki, Shinya; Nozawa, Michihito; Kuwada, Chiaki; Kise, Yoshitaka; Ariji, Eiichiro; Ariji, Yoshiko.
Afiliación
  • Fukuda M; Department of Oral Radiology, School of Dentistry, Osaka Dental University, 1-5-17 Otemae, Chuo-Ku, Osaka, Japan. fukuda-m@cc.osaka-dent.ac.jp.
  • Kotaki S; Department of Oral Radiology, School of Dentistry, Osaka Dental University, 1-5-17 Otemae, Chuo-Ku, Osaka, Japan.
  • Nozawa M; Department of Oral Radiology, School of Dentistry, Osaka Dental University, 1-5-17 Otemae, Chuo-Ku, Osaka, Japan.
  • Kuwada C; Department of Oral and Maxillofacial Radiology, Aichi-Gakuin University School of Dentistry, Nagoya, Japan.
  • Kise Y; Department of Oral and Maxillofacial Radiology, Aichi-Gakuin University School of Dentistry, Nagoya, Japan.
  • Ariji E; Department of Oral and Maxillofacial Radiology, Aichi-Gakuin University School of Dentistry, Nagoya, Japan.
  • Ariji Y; Department of Oral Radiology, School of Dentistry, Osaka Dental University, 1-5-17 Otemae, Chuo-Ku, Osaka, Japan.
Odontology ; 2024 Apr 12.
Article en En | MEDLINE | ID: mdl-38607582
ABSTRACT
The objectives of this study were to create a mutual conversion system between contrast-enhanced computed tomography (CECT) and non-CECT images using a cycle generative adversarial network (cycleGAN) for the internal jugular region. Image patches were cropped from CT images in 25 patients who underwent both CECT and non-CECT imaging. Using a cycleGAN, synthetic CECT and non-CECT images were generated from original non-CECT and CECT images, respectively. The peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) were calculated. Visual Turing tests were used to determine whether oral and maxillofacial radiologists could tell the difference between synthetic versus original images, and receiver operating characteristic (ROC) analyses were used to assess the radiologists' performances in discriminating lymph nodes from blood vessels. The PSNR of non-CECT images was higher than that of CECT images, while the SSIM was higher in CECT images. The Visual Turing test showed a higher perceptual quality in CECT images. The area under the ROC curve showed almost perfect performances in synthetic as well as original CECT images. In conclusion, synthetic CECT images created by cycleGAN appeared to have the potential to provide effective information in patients who could not receive contrast enhancement.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Odontology Asunto de la revista: ODONTOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Japón
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Odontology Asunto de la revista: ODONTOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Japón